Why Automatic Understanding?

Ryszard Tadeusiewicz, Marek
R. Ogiela

University of Mining and
Metallurgy

Cracow, Poland

Typical applications of
Artificial Intelligence (AI) methods in biomedicine (e.g. medical
diagnostics), in the area of engineering problems (e.g. control systems) and
also in intelligent economical information systems includes some traditional
techniques: intelligent data processing and analysis, pattern recognition,
neural networks, genetic algorithms and expert systems. Data processing and
analysis give us better description of the objects or processes under
consideration. Pattern recognition give us possibilities of its
classification – for example in case of automatic diagnostics. Neural
network helps us to build behavioral models for control or forecasting.
Genetic algorithms can solve optimization problems. Expert systems can
advise us, what we ought to do in particular situations. This short outlook
presents general view over the typical AI landscape.

In many biomedical,
economical, and engineering problems it is enough. If we can solve presented
problems and if we can build AI tools for intelligent data analysis,
recognition and modeling – we are happy. This is true, but definitely not in
all situations. Sometimes solving of complex problems leads to the necessity
of understanding some signals, patterns and situations instead of
simple processing, classification and interpretation. In fact understanding
of the problem is first necessary step for intelligent solving of the
problem, when we use natural (not artificial) intelligence. Understanding of
the problem is not special case of signal processing – it needs also some
knowledge and demands special type of data processing. Details of natural
understanding are very complicated and obscure, therefore we can talking
about understanding in terms of psychology and in frames of cognitive
science, although in fact we can not understood the natural understanding
process!

Nevertheless we can propose
effective methods of artificial imitation of understanding. Although it
sounds strange - in fact it is definitely possible to build up the system
for automatic understanding of selected data, signals and situations. This
fact was proven by the authors in many previous papers and books on the base
of many examples of medical images. If computer powered by special AI
programs can understood the nature of disease on the base of analysis of
features of some medical images it can be applied also to the solving of
other complex problems, demanding automatic understanding as a part of its
automatic solving. In the paper we describe the general methodology of the
automatic understanding and we show how to use this methodology for solving
selected biomedical, economical and also engineering problems.

Professor
Ryszard Tadeusiewiczstudied at the Electrical Engineering Department of
the University of Mining and Metallurgy in Krakow from which he graduated
(with honors) in 1971. Additionally, after receiving his degree in Automatic
Control Engineering, he studied at the Faculty of Medicine at the Medical
Academy in Krakow, as well as undertook studies in the field of mathematical
and computer methods in economics. Since April 1971 he has done research in
the areas of bio-cybernetics, automatic control engineering, and computer
science. In 1975 he was awarded the Ph.D. degree, and in 1981 the degree of
Doctor of Sciences (habilitation). In 1986 he became Professor and in 1991
the Full Professor at the University of Mining and Metallurgy. He obtained 9
Honorary Doctor awards from Polish and foreign Universities.
He has written and published over 500 scientific papers, which were
published in prestigious Polish and foreign scientific journals as well as
numerous conference presentations - both national and international. Prof.
Tadeusiewicz also wrote over 70 scientific monographs and books, among them
are highly popular textbooks (which had many reprints). He was supervisor of
44 doctoral thesis and reviewer of more than 200 doctoral thesis. In 2003
all Polish scientists elected him to be the Member of Central Committee for
Scientific Degrees and Scientific Titles (organ by Prime Minister of Polish
Government).
In 1996, in universal and secret elections he was elected the Vice-Rector
for Science of the University of Mining and Metallurgy, and in January 1998
its Rector. He was re-elected 1999 for the term 1999 - 2002 and again 2002
for the term 2002-2005. In February 1998 Prof.Tadeusiewicz was elected the
Corresponding Member of Polish Academy of Sciences and Arts (PAU), in
February 2000 he become Foreigner Member of Russian Academy of Natural
Sciences, in May 2002 he was elected for the grade Corresponding Member of
Polish Academy of Sciences (PAN), and in September 2005 he become fellow
World Academy of Art and Science (San Francisco).

Professor
Marek R. Ogiela works in Bio-Cybernetics laboratory at the AGH
University of Science and Technology in Krakow. In 1992 graduated from the
Mathematics and Physics Department at the Jagiellonian University. In 1996
for his honours doctoral thesis on syntactic methods of analysis and image
recognition he was awarded the title of Doctor of Control Engineering and
Robotics at the Faculty of Electrical, Automatic Control, Computer Science
and Electronic Engineering of the AGH University of Science and Technology.
In 2001 he was awarded the title of Doctor Habilitated in Computer Science
for his research on medical image automatic analysis and understanding. In
2005 he received a professor title in technical sciences. Member of numerous
world scientific associations as well as of the Forecast Committee `Poland
2000 Plus´ of the Polish Academy of Science and member of Interdisciplinary
Scientific Committee of the Polish Academy of Arts and Sciences (Bio
cybernetics and Biomedical Engineering Section). Author of more than 90
scientific international publications on pattern recognition and image
understanding, artificial intelligence, IT systems and biocybernetics.
Author of recognised monographs in the field of cryptography and IT
techniques; author of an innovative approach to cognitive medical image
analysis. For his achievements in these fields he was awarded many
prestigious scientific honours, including Prof. Takliński´s award (twice)
and the first winner of Prof. Engel`s award, nominated in the category
Science to the Silver Nike award in 2003. Reviewer of world scientific
periodicals, including: IEEE Transactions on Systems, Man, and Cybernetics,
Artificial Intelligence in Medicine Journal and Journal of Intelligent &
Robotic Systems. Currently employed by AGH at the post of Automatics where
he conducts vast scientific research on Medical Imaging and information
encrypting.